Integration

System Integration and Migration Validation

Data mapping, transformation, reconciliation, and validation for moving information between platforms without treating a successful upload as proof the migration was correct.

System path
  1. Source profiling
  2. Field mapping
  3. Transformation
  4. Control totals
  5. Rejected records
  6. Final validation

The operational problem

Moving operational and financial data between platforms: accounting systems, property platforms, payment processors, Microsoft 365, and internal tools, where the cost of a silently wrong migration exceeds the cost of the migration itself.

Why the existing process failed

The default approach exports, massages, uploads, and declares victory when the importer stops complaining. Record counts pass while balances drift, categories collapse, and history quietly loses meaning.

What was built

Migration and integration tooling built around validation: source profiling before mapping, explicit field mappings and transformation rules, control totals at each stage, rejected-record handling with reasons, repeatable reruns, and post-migration reconciliation against the source system.

What the system automates, calculates, and controls

Extraction, transformation, load, and the evidence that the result matches the source: counts, totals, and balance ties by entity and period.

Where human judgment remains

Mapping decisions and the disposition of rejected records: the system refuses to guess what a person has not decided.

How correctness was tested

Every migration carries its own proof: control-total reports and reconciliations that either tie or name exactly what does not.

What changed

Cutovers became decisions made on evidence, and integrations stopped depending on the hope that two systems agree.

Disclosure

Client work across several environments; names withheld.

Methods and research context

Stack

PythonSQLQuickBooks integrationMicrosoft 365CSV/ERP exports